Generative AI Specialist – Humanities, English, Spanish

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October 3

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Innodata Inc.

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(NASDAQ: INOD) Innodata is a global data engineering company delivering the promise of AI to many of the world’s most prestigious companies. We provide AI-enabled software platforms and managed services for AI data collection/annotation, AI digital transformation, and industry-specific business processes. Our low-code Innodata AI technology platform is at the core of our offerings. In every relationship, we honor our 30+ year legacy delivering the highest quality data and outstanding service to our customers.

1001 - 5000 employees

📋 Description

• Evaluation: Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. • Annotation Labeling: Labeling elements of a piece of content rather than the content as a whole. • Classification: Assigning predefined categories or labels to items. • Content Quality: Evaluating the perceived quality and/or appropriateness of content. • Content Understanding: Generating labels to advance understanding of a concept, trend etc. • Data Augmentation: Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images, generating new text, or altering audio/video signals. • Grading: Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. • Identification Labeling: Labeling model outputs to identify specific characteristics of content. • Preference Ranking: Ordering or ranking items based on a set of preferences or criteria. • Prompt Generation: Creating prompts or questions that will be used to generate responses from a language model or other AI systems. • Relevance Evaluation: Projects that evaluate the relevance of content based on a relevancy scale. • Response Generation: Generating responses to prompts or questions using a language model or other AI systems. • Response Rewrite: Rewriting existing text while preserving the original meaning. • Response Summarization: Producing concise summaries of longer pieces of text or data. • Similarity Evaluation: Comparing content to drive determinations. • Transcription: Converting spoken language or audio content into written text. • Translation: Converting text or spoken language from one language to another. • Data Collection: Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models.

🎯 Requirements

• A Bachelor’s degree or higher in a humanities specialization is required. • Advanced degrees are strongly preferred (Master’s or PhD) • Professional or Expert level proficiency (C1/C2) in English and Spanish

🏖️ Benefits

• Flexible work arrangements